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Development of a Prognostic Model of the User’s Information image Using Automated Tools for processing Data from Social Networks 4th

Development of a Prognostic Model of the User’s Information...

引用

4th International conference on Digital Transformation and Global Society, DTGS 2019

作者： Tropnikov, Alexandr Uglova, Anna Nizomutdinov, Boris St. Petersburg199034 Russia The Herzen State Pedagogical University of Russia St. Petersburg191186 Russia

ISBN: (纸本)9783030378578

This article presents a first phase’s results of research project, dedicated to developing prognostic models of User’s image with the automated Social Networks data processing methods. A pilot study carried out a comparative analysis of automatic methods for analyzing textual and visual data, which constituting a User’s informational image. We used a correlation analysis of data, which was obtained by using parsing methods and the results of psycho diagnostic research. As a result, multiple relationships with the socio-psychological characteristics of the respondents were identified. Based on obtained data, we have concluded about acceptable predictive capabilities of automated analysis. © 2019, Springer Nature Switzerland AG.

关键词： Automation

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VCIP 2019 conference Events

VCIP 2019 Conference Events

引用

IEEE visual communications and image processing (VCIP)

Provides a schedule of conference events and a listing of which papers were presented in each session.

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Design and implementation of a multistage image compression and reconstruction system based on the orthogonal matching pursuit using FPGA 14

Design and implementation of a multistage image compression ...

引用

14th International conference on Computer Engineering and Systems, ICCES 2019

作者： Ahmed, Mohamed Mahran Bedour, Hassan Hassan, Sara M. Faculty of Engineering Ain Shames University Computers and Systems Engineering Department Cairo Egypt Modern Academy for Engineering and Technology Electronics and Communications Engineering Department Cairo Egypt

ISBN: (数字)9781728152608

ISBN: (纸本)9781728152608

Due to the vast developments in the media communication field and the quality of the visual imaging, image data compression has been one of the most interesting field. The main purpose of the image compression is to produce a very low bit rate while achieving a high quality of the reconstructed images. image compression are used for all fields of media communication such as medical image recognition, multimedia, digital image processing. There are different algorithms for compression and reconstruction. One of these methods is the Orthogonal Matching Pursuit that is used mainly in the reconstruction of the radar signal. This paper discloses a new methodology for image compression and reconstruction to enhance the performance while at the same time reducing the bit data size. This kind of reconstruction algorithm is based upon multistage compression and OMP reconstruction. The Matlab Simulation and the FPGA implementation will be provided in this paper to validate the concept of this paper. © 2019 IEEE.

关键词： image compression

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A Fast Vision-Based Indoor Localization Method Using BoVW-Based image Retrieval 6th

A Fast Vision-Based Indoor Localization Method Using BoVW-Ba...

引用

6th International conference on communications, Signal processing, and Systems (ICCSPS)

作者： Ma, Lin Jia, Tong Tan, Xuezhi Harbin Inst Technol Commun Res Ctr Harbin Heilongjiang Peoples R China China Minist Publ Secur Key Lab Police Wireless Digital Commun Harbin Heilongjiang Peoples R China

ISBN: (纸本)9789811065712;9789811065705

With the increasing demand for indoor localization service in our daily life, vision-based indoor localization has become a hot topic since image recording and application are very popular in the indoor environment. Based on the epipolar geometry algorithm, more images are required in the database to achieve better localization performance, which would inevitably lead to high time consuming for image retrieval. Therefore, in this paper we propose a vision-based indoor localization method by using the BoVW (Bag of visual Word)- based image retrieval method, which could achieve less time consuming and good localization performance. The experiment results show that the localization error of the system by utilizing our proposed method could achieve an accuracy of less than 2 meters by a chance of 75%, while the time for localization sharply decreases by 60%. Compared with the traditional localization system, the proposed method could make a balance between the localization accuracy and efficiency in practice.

关键词： Indoor localization Vision-based image retrieval BoVW algorithm Epipolar geometry

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3D image Reconstruction with Single-Slice CT using Improved Marching Cube Algorithm

3D Image Reconstruction with Single-Slice CT using Improved ...

引用

International Biomedical Instrumentation and Technology conference (IBITeC)

作者： Purnama, Ignatius Luddy Indra Tontowi, Alva Edy Herianto Gadjah Mada Univ Dept Mech & Ind Engn Yogyakarta Indonesia Atma Jaya Yogyakarta Univ Fac Ind Technol Yogyakarta Indonesia

ISBN: (纸本)9781728133393

Single-slice CT is still widely used in many hospitals because it prolongs the life cycle of the CT device components, especially that of x-ray. Using CT 3D image, it can be very helpful for a doctor in diagnosing medical information. In the development of 3D image reconstruction and computer technology, it is possible for the doctor to communicate with the patient through gadget media. This paper presents the determination of the threshold in single-slice Computerized Tomography (CT) for interactive 3D image reconstruction without user interface. The 3D image reconstruction method is the improved marching cube algorithm. The medical image object that consists of skull bone and sternum-pelvis in Digital Imaging and communications in Medicine (DICOM) format is taken from single-slice CT. The resulting threshold for bone 3D image object is 200, except for the 3D image with quantity slice less than 10 can not be reconstructed. The difference in the surface volume and surface area between the 3D image reconstruction output from InVesalius software and project, for skull bone and sternum-pelvis is less than 0.5%. The justification of the visual shape match from three radiology doctors for skull bone and sternum-pelvis is approximately 99% match. processing time to reconstruct the 3D image is around five minutes.

关键词： bone mesh surface reconstruction single-slice CT threshold

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Multi-scale Neural Style Transfer Based on Deep Semantic Matching 4th

Multi-scale Neural Style Transfer Based on Deep Semantic Mat...

引用

4th International conference on Cognitive Systems and Information processing (ICCSIP)

作者： Yu, Jiachen Jin, Li Chen, Jiayi Tian, Zhiqiang Lan, Xuguang Xi An Jiao Tong Univ Sch Software Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Shaanxi Peoples R China

ISBN: (纸本)9789811379864;9789811379857

Existing Neural Style Transfer (NST) algorithms do not migrate styles well to a reasonable location where the output image can render the correct spatial structure of the object being painted. We propose a deep semantic matching-based multi-scale (DSM-MS) neural style transfer method, which can achieve the reasonable transfer of styles guided by the prior spatial segmentation and illumination information of input images. First, according to real drawing process, before an artist decides how to paint a stroke, he/she needs to observe and then understand subjects, segmenting space into different regions, objects and structures and analyzing the illumination conditions on each object. To simulate the two visual cognition processes, we define a deep semantic space (DSS) and propose a method for calculating DSSs using manual image segmentation, automatic illumination estimation and convolutional neural network (CNN). Second, we define a loss function, named deep semantic loss, which uses DSS to guide reasonable style transfer. Third, we propose a multi-scale optimization strategy for improving the efficiency of our method. Finally, we achieve an interdisciplinary application of our method for the first time-painterly rendering 3D scenes by neural style transfer. The experimental results show that our method can synthesize images in better original structures, with more reasonable placement of each styles and visual aesthetic feeling.

关键词： Neural style transfer image segmentation Illumination estimation Patch matching

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Kernelized Target Representation for visual Tracking with Sparse Constraint 4

Kernelized Target Representation for Visual Tracking with Sp...

引用

4th IEEE International conference on image, Vision and Computing, ICIVC 2019

作者： Wang, Yuanyun Wang, Jun Wu, Zhaoming Tian, Wei Deng, Chengzhi Wang, Shengqian Nanchang Institute of Technology Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang330099 China

ISBN: (纸本)9781728123257

Robust visual tracking is a challenging task due to factors motion blur, fast motion, partial occlusion and illumination variation. Existing tracking algorithms represent a target candidate by templates or a linear combination of them with some constraints such as sparse coding. While the high computational cost restricts the tracking speed with sparse constraint since many trivial templates are introduced. Due to affecting by complicated appearance variations, the relationship between a target candidate and the corresponding target templates is not linear. Maybe it is nonlinear or complex. In this paper, we present a kernelized target representation model with sparsity constraint for visual tracking. Namely, a target candidate is represented by a nonlinear combination of templates with sparsity constraint. The proposed appearance model have the advantages of sparse coding and kernel method, which is robust to outliers and represents a target candidate in a high feature space. A novel tracker is proposed upon the presented appearance model. Superior experimental results are achieved against state-of-the-art trackers on some challenging sequences. © 2019 IEEE.

关键词： Target tracking

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Video Anomaly Detection Using Open Data Filter and Domain Adaptation

Video Anomaly Detection Using Open Data Filter and Domain Ad...

引用

IEEE visual communications and image processing (VCIP)

作者： Chen Zhang Guorong Li Li Su Weigang Zhang Qingming Huang School of Computer Science and Technology UCAS Beijing China Key Lab of Big Data Mining and Knowledge Management UCAS Beijing China Harbin Institute of Technology Weihai China Key Lab of Intelligent Information Processing ICT CAS Beijing China

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

Video anomaly detection is a very challenging task because of the rarity, openness, and the definition of the anomalies. Researchers pay more attention to the characteristics of anomalies and have proposed a variety of anomaly detection models. However, most existing methods only use normal events to construct anomaly detection models and ignore the diversity and openness of normal events. Actually, because real-world video data often have an open-ended distribution, some normal patterns hardly ever appeared in the training data. In addition, analogous to human experience in identifying anomalies, rare abnormal events can play a certain role in the detection of similar abnormal events in the dataset. Therefore, assuming that a small number of abnormal events are known, we propose a novel supervised anomaly detection model which explicitly detects open normal events and open abnormal events in the dataset and treats open data and seen data with different classifiers. First, we use the training video to train an imbalanced classifier as the seen data classifier. Then, during the testing phase, an open data filter module isused to divide the test data into seen data and open data. Finally, we directly use the seen data classifier to generate anomaly scores for the seen test data. For the open test data, we adopt a domain adaptation method to reduce the distribution difference between it and the training data and train a new classifier to score for it. Extensive experimental results prove the effectiveness of our model.

关键词： Training Training data Anomaly detection Feature extraction Data models Testing Adaptation models

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Android Oriented image visualization Exploratory Search 5th

Android Oriented Image Visualization Exploratory Search

引用

5th International conference of Pioneer Computer Scientists, Engineers and Educators, ICPCSEE 2019

作者： Ouyang, Jianquan He, Hao Chu, Minnan Chen, Dong Tang, Huanrong College of Information Engineering Xiangtan University Xiangtan411105 China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education College of Information Engineering Xiangtan University Xiangtan411105 China

ISBN: (纸本)9789811501203

When using traditional image search engines, smartphone users often complain about their poor user interface including poor user experience, and weak interaction. Moreover, users are unable to find a desired picture partly due to the unclear key words. This paper proposes the word-bag co-occurrence scheme by defining the correlation between images. Through exploratory search, the search range can be expanded and help users refine retrieval of the expected images. Firstly, the proposed scheme applied the bag of visual words (BoVW) vector by processing images on Hadoop. Secondly, similarity matrix was constructed to organize the image data. Finally, the images in which users were interested was visually displayed on the android mobile phone via exploratory search. Comparing the proposed method to current methods by testing with image data sets on imageNet, the experimental results show that the former is superior to the latter on visual representation, and the proposed scheme can provide a better user experience. © Springer Nature Singapore Pte Ltd. 2019.

关键词： visualization

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14th International conference on Pattern Recognition and Information processing, PRIP 2019

14th International conference on Pattern Recognition and Inf...

引用

14th International conference on Pattern Recognition and Information processing, PRIP 2019

ISBN: (纸本)9783030354299

The proceedings contain 25 papers. The special focus in this conference is on Pattern Recognition and Information processing. The topics include: Brands and Caps Labeling Recognition in images Using Deep Learning;influence of Control Parameters and the Size of Biomedical image Datasets on the Success of Adversarial Attacks;performance of Sequential Tests for Random Data Monitoring Under Distortion;equipment Condition Identification Based on Telemetry Signal Clustering;robots’ Vision Humanization Through Machine-Learning Based Artificial visual Attention;automatic Analysis of Moving Particles by Total Internal Reflection Fluorescence Microscopy;fuzzy Morphological Filters for processing of Printed Circuit Board images;Detection of Bulbar Dysfunction in ALS Patients Based on Running Speech Test;thresholding Neural Network image Enhancement Based on 2-D Non-separable Quaternionic Filter Bank;method of Creating the 3D Face Model of Character Based on Textures Maps Module;shadow Detection in Satellite images by Computing Its Characteristics;nearest Convex Hull Classifier with Simplified Proximity Measurement;image Semantic Segmentation Based on Convolutional Neural Networks for Monitoring Agricultural Vegetation;reliability Analysis Based on Incompletely Specified Data;semantic-Based Linguistic Platform for Big Data processing;cell Nuclei Counting and Segmentation for Histological image Analysis;robust Person Tracking Algorithm Based on Convolutional Neural Network for Indoor Video Surveillance Systems;modeling of Intelligent Systems Architecture Based on the Brain Topology;temporal Convolutional and Recurrent Networks for image Captioning;Video-Based Content Extraction Algorithm from Bank Cards for iOS Mobile Devices;FPGA Based Arbiter Physical Unclonable Function Implementation with Reduced Hardware Overhead;preface.

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